{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 散点图绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. 导包\n",
    "import matplotlib.pyplot as plt\n",
    "# 2. 数据准备\n",
    "x = [225.98, 247.07, 253.14, 457.85, 241.58, 301.01,  20.67, 288.64,\n",
    "     163.56, 120.06, 207.83, 342.75, 147.9,  53.06, 224.72,  29.51,\n",
    "     21.61, 483.21, 245.25, 399.25, 343.35]\n",
    "\n",
    "y = [196.63, 203.88, 210.75, 372.74, 202.41, 247.61,  24.9, 239.34,\n",
    "     140.32, 104.15, 176.84, 288.23, 128.79,  49.64, 191.74,  33.1,\n",
    "     30.74, 400.02, 205.35, 330.64, 283.45]\n",
    "\n",
    "# 3. 创建画布\n",
    "plt.figure(figsize=(20,8), dpi=100)\n",
    "# 4. 绘图\n",
    "plt.scatter(x, y)\n",
    "# 5. 显示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 柱状图绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JutzRmZMvGtH/is+srY9MUpc7WnLyReOFxLyUn4prz5HynGD45yfNmtXfcq9X7mihLl/0s9zrlTsq0Ctf9LPcwyD1iwpUKrSa9SPlDq38NHPmzBH7nLLPjRiq+en1119veM3+UKM/xPxG0unAkma2W27bS8D+ZnZ1Yd9jgWOGt4VBEARBEARBEARBEARBEARBEIwyVjSz5wa680iORHkBWDP7IqkKTAReLNn3ZOCUwrbFgRlD1rrg7bAw8CywIvDWzH/BWCT6RdCI6BtBGdEvgjKiXwRlRL8Iyoh+ETQi+kZQRvSLoIzoF0EZ0S9GPgsDzw/mgJFsRPk9cISkplQX5f1AN/DX4o5m1oFHQOWZOfRNDN4KqodYv25m8ZwCIPpF0JjoG0EZ0S+CMqJfBGVEvwjKiH4RNCL6RlBG9IugjOgXQRnRL0YFg34uI7mw/FTgv8BxklYEvg38ysza52+zgiAIgiAIgiAIgiAIgiAIgiBYEBixRhQzqwGfBrYHnsTr6hw2XxsVBEEQBEEQBEEQBEEQBEEQBMECw0hO54WZ/QV43/xuRzDP6QCOY84UbMGCTfSLoBHRN4Iyol8EZUS/CMqIfhGUEf0iaET0jaCM6BdBGdEvgjKiX4xBZGbzuw1BEARBEARBEARBEARBEARBEAQjjhGbzisIgiAIgiAIgiAIgiAIgiAIgmB+EkaUIAiCIAiCIAiCIAiCIAiCIAiCEsKIMgqRNF5Sw2cnqSppfMn2EV0DZ27IGbY+K6lJ0gRJ75S0vqQdJR0s6SeSpkr6/HC1ZUFCUnPxOadt4yVNyW37IUDhxQAAIABJREFUoaRNh7+FYwNJbZImS2oe5HHrSlrsLV5zUO+vpImSFn4r1xrkddrKtkl61wCPX0XStvO+ZSOfNE5qfrdjoBSftaRJ86stQRC8dSTtIul/BrH/OyR9d4D7qvB92eFcfwZDg6StFtS5OgiCgSNpTUlLzu92BKOXpI87XNLiuW07SvrA/GxXEARvnxAIRie/Bv4o6Z707zlJz2bfgXuA6/MHSDoQuLZ4Ikl7S7pueJoNko6S9KnCto0kPZn7vn2DCeYe4NMl5/ydpE82uF5z7vPzkj6YPq8j6fn0uSqppXDcbcBzwL3AVcDZwE+B8cCfgZOAPw3glscMkioDUSIkg0epUlXS5yWdXthW3Pco4GVJL0l6SFIH8HdgTeAESRtKWgjYC3hmAO3ZTtLrkqalf49Lmja34xYAJgM3ARsN9ABJVeBG4DMD2HcbScV35AOS7h9EGw8CnpC0yFyu9XVJ7859nyLpwsI+l0naueTYScAzkk6StETathDwK+CSARpxPgJcNID9xiLHA+2Spkt6ueRfp6SPFA+SdICkywrbqpJM0sTC9mblnAAkjZPUWmYAzG+XtLSk2yWtmr5vA9yZjTmSVgb+Jmm5kvNMknRd7lytxXkimDdIOrO4LhjEsb+T9Om0/plU+G251J/K+uXLkmZK+nOD894h6ak0BxX/PS7pX2+lvcHgkXS3pBfTGu6NND4DfBNYo8ExbZJOzf8DjgEOL2w/XdLnCsdWgQckbZnbfCOwxzy/uWBISHLFFSXryz2BDfs57jJJe5dsv0PSWpLOLfSLYIQg6WpJP34Lxz0pafdBHjNdDeTOkn0Xlzvklf1bWNISacwJRhbn4HJmQ9LaY7fCtqOzMaJk/AlGGZK2lrR6+nyCpPcN4vAasAJwXjp+PPATIIxzYwRJKyY5Y9Hcto0l/XMAx7ZKuk9hVBuVjOrIhAWRNDEfV9j8RaATuLCw7yZmdnf6+nvgVElLmdl/c7t1ADMbXGsn4If4YH8D8AUza3+bt/B34BxJdwMfBk7DJ5nFJb0MHAl8N/1/X+HYP+DK2ysK2xveA/AzSe8HLN3HxZI6gRZgSUkP4cbEG4GvFs65l5ndBCD3SL/bzAbkxThG2QD4raQ38b8n+N+xGXgjfa8CCwHvBR4HkPRlYKaZXQL8F9hX0rfM7FVJ6wK/lLSvmf0ewMyOlxtrus3sREmPAduZ2dOSDscNWTsBZ5pZH0WWpBuAtYAZwPLABcAtwANmtmnaZxvcULNAIanNzGbnNh0CnGdmdxX2qwDjzWxW8Rxm1iM3TgwkeuVNYHbunM1AF9DdTxuXTcd04PPTfsApQKfqEQQCFgZmm1n23r8G/FrShrjxYxIwLr3fGSsAm0j6mJntk7unJ1M/PBx4TG7k2wm4E/i6mXUV2nhSatcLhea/XLjeROARM5vDgDCWMLNvAN9o9LukZ/Hnnn2/EXgHsBgwPv3NfgbsACyRdrs7yZ4tuJJ0b+DbaZHakc53GbCLpG78XZ+B950W4DDgcjP7j6RbgamSVjWz2yTtASwHPA98DPgnsKPcSPOSmV2Z2vA0sEo61/fwefdASfl3qA34tZntOri/WpAhaS/go8BWku4qrE9I7/Q6+DoBADM7L7dLBz6vHI0/rycLvwEsbWY1CqQ1zqENmtYFXIOvWYosgStjg+GhE9gNX8N9xszekLQFPs7vnZTeSwPtwLvNrBOfb7YFPpHOcTSuvPhB+r4bcBs+dxTXj9sAKwGPSGpJ51uKtCZNirFx82A9HAwd/8Sf41HAdyRdDayOP9f/SMocsi4urOs7gDfTM24FusysB59XarhD1Uol66lg/tOFv8+D5c30b55fK61bn8f7VSY3LQq8jvenCjAOX+f8Y5BtCOYRks7BnaHyLAa8X9JBhe3/NrPN0+e18HHi8tzvWwEvJb3BNsCgDHTBiGMx4DxJlwJbAtdKmom//034WmMWMAE4w8y+DSDp58B6JJk1yToL4WuVH0r6IS5j/maY7yeYB0hqBXrw9Sl4H8joBqppHdEM1MxsDt2HmXVImo47iBd1nsEIJ4woo49bgDOAV3Pb3om/sFvmti0PfFTuaVsxswckrW1m/5W0TjoHuFC6mKSp6fspZvYruWfuhcAuwBPAlbiR4YS303gzuzpZ4qeb2WXAZUmBebGZrS3paODevJJE7v3bDfwvaZCSdATw8bTLe4AfScoWtJPN7M10vT1y53ka2MHMHpO0BnCTma3doKldhe9PA4tIWsHMnkvnqwLNC4ogZWZ/wg0Yvcg9OHc2s+37OfQ9wAeBS/AoqleBXXFhdHdgceDBuV1f0mm48rMGrA/8Q9KvgO+b2T1pt5nAt83sYknH4v2mghvMMm+htZnz+S4IPC3JcGFuIVzJv1p6L/JMAF5I79jFuIGsJ/fbG4BJOiR3TBUfZ1YASO9XLe23Lt5vrkr7LpmuuShwjpkdkTvP3bixo4YrLQz4dvqXofTbkbiRFzM7O72PZmZbSPoEsK2Z7dd7kBt/rjKzG4p/GDN7TtJR+GL5MHxR9DB1oTfPA8ChZvbzdN6zgYfM7Cf5nSRtBHyo5Pgxhdz7/7fUlQJFlqHv33EnPKrsXuBS4MfA34Az8cgocOFkW+oKrHNw4/tZwD1mdmHa77BkoJsObGlmjxUvbmbflXQFbqxdLrXlBkmXA5/C59Q2fKHbkjuuO/XxjdP3I/E+l7/3/RhEJFfQF0kb4/P6dsAWwNWSPm5meeVUBX/nD8H7x9+TMX0ffFxaCTfCvQE0STrTzE5Lx/b2R0mbmtnU9PnjuGHmYRrPBXPzIA0P0+EjE1I3wRUYVeD7+DixN3A/Pi6fkAwe4M9+Nu54syX+vCcBD+FrklXwfmdAMS3oEXif+jDwgzRvroAb6sGf/ThJ7zKzNwhGHGb2kjwC//PAd/Bx4kAzuzPbJ60Rs+jTdwCr4gquNfDx6CqgQ1IXsCxwOz5eNOP9b9Vhup1gYHRTX6sOhh7K1y5v+1pJPuxNIZqcNbqAdczs6UFeMxg6FgOOzdaWaY7Zwcyuye8kd2Q9M7epB+hOytJMV/Ea3p9+CRwiaQMzK414DUYFV+OOPocCy5jZ68Ai0KsD2dTMytK7rwgcmcmckm4CzjKz/0vfbyA3NgSjjiNxHWnGfaoHno3D9VUP4OuFg4Fbk1PfJtTXtBkfTPJkxgRgn0zPEIxMwogy+jDcAHJp+n4pMBUXFhfHFT7P4ylWtsO9e89M3rMTkvJyf9yTe/e0z6bAt3BPvcwTeE3gCjO7BTyUHfe4ePs3YPaLsu2S3otPUsWwtl+k++oBlpX0NVwgugNfpJwFnI+n2bqP5OmelJubUleSTACuSdbjN/G/x/24QDwBON7M8il5zpKUtyy/gXsmZimkmtJ53j+oP8AoRtI4XLi8NSk3B8KZwAGS3mtmD0q6EtgweWnsBZxsZq+WHHdQMnxkdSluw5XxOwCPAD/HJ6rnc8d0Accn5efyuIK2CXgFeDnt81Y81UY9ZrYs9EaF/Bn44QAiq/J5XJcGXgLWNrMXGx2QhI/7cQ8s8CiFy81seUlr4wbTdSUdiT+/fBuztEvL4QrOKWZ2c38NlLQ+7iX8T/w5Z+yivjVzVqBuyMkfPx7vh0cBdwGr4cblU4CjkmH3MjPLDAFduGLta7jQtBLwlKR90++L4sbeFjzd3Kn9tX8M8C9gpTJPf+iNRMkrnJvw8foiXGF1ETAFN6zeD2yGv9u/StvmZqReGx+/54gYSJ6As8zsKXnqjfuBT6Z9d8QNPIc3GsvM7DZ83OmPMkNbMBckfRRfvxxkZn8B/iJpTTxV6ReyKFoz+wPwh2QYvcHM7kyKqFNwRcWNwHfT9mKEXBP+fFYFbpQ0JQm0ewJP0f+zew73TD0Ad6LoSudbBe8/kc5r+Mie09a4QnwTfO01GR8n7gf+nBxzMmrpuO/gCvDV8fH/AmB73DDbAnwi//6nfvlh4AIzuwK4IjkeXWlmqw/ZHQbzHDO7LEWgwNyV5O/G07VNwtcl/zKz3pQrydHs82WG+mBkIo9s3gbYGZhmZicO4bXWwOXpKcAReWNdMCq4FXg0970Z+Jo8+vlm4GNmdj4uZ+RTxtWArwCfw53JppDW/yli8lPAepJeM7OyqNZgBJOcxC4CpuGRYmsx8FTuNVz/lkW/rgisrXpdthVJab6C0YeZHQccJ6+b9F8zWzf7LeklrjKzdQqHdQIHF6Lp50DSncxd9g3mM2FEGX18HXjRzNbPNkj6Hu4FfnBu29LAicmL4pq07UbgdNzI8KaZPZSUmq+mz6+k3zCzO3AjBZKWwheHF7+dhstzUu+BRyP8Ffcuz1JDLYQbQF7BU0a1AVPNbOcsVYqklXCv4fPx9CrPp3bPAp5Kny13D18qacMk4E4zW2Uuza3iKXtuB1Y2syfkUT2/A/ZNURmZV9GCxJK40mrAxcjN7OHU974OfBZXWnbI03x1UI+KKvITq6fzwsyuB5DnJm01szkU4rhSJB+JIlxRujjeh8EjtxZkvop7v5wiaQV8QbhKzoO3EVke+tfnst+KwIvU03ZdjCutflWybyMl5tnANWZ2s6SvAxOyEOkS3oOHTB9Mvc5XFfhlSSRKn5o+8loZfwAew9O7PIYrZ/czs+2SAHQILkRNB8jGVHmtlPtxJd35Zva8pM/gacHWH4SRcbRzHHCopEYe2VXS3z0ZsG/B55ancA/xjXHDxo640fsg3Di+AV6/5AO4UvOqdJ5d0lyyUopY2AE3sJukVcwsn4f2U8ARkr5sZlclAx9mVpOneXwSeC7nPXRAipb8JR49B+4NdMdb//MEeZLH99H4WmCKmfXWajOzL0r6KnCbpN/h/eASM+sonGYNYHczOyoXGQBuDH0BX2NASiGY5u+98HSen8IVa6vjz3iOXPTylI/34pFxJ+CK9+m49+E3cMNoRdKWoSwbNt6Fp/j8L/Df9Iw2xuf8HYDT5LnK/54ikYUrMT6Ez12P4mnfvowbx64FrsOj0j5nZvelMf0MPBXp4pJewNco4/BI5KcLbbrPzN5SLZ9g6Ejywxa4EmI2vsYxPL1vcZ66GMDMbgduT+uEm8zscnm04odxOWXZ9HsX7pCxrpk9PBz3EwyKdeV1UbbGx4ypuCPEzfKsBssypxdwEzAxGV0yhMvVz/VzrR2S88xWeEqn23H59Inek3j9pg4rSeWS2ydLHdfd337B0GFm50jaQ9L2uH5iU9zLfFF8nnhJXj9tIzPLR6IYcK6ZfS05gewAvA/YQtKhuCz0CH0NNMHo4Tk8wvUmST8CNmfgRpQK7oSTpev6NS7bZnWIryVqU48Z1LfW7vgGu2U1NjcBLjKzSQ32u4++GYeCEciCpgAe9ZjZaZIWVT391i/xxVdN0gn4gv91M/so7mkHQFLuVfB0GOvgeT6fxoXLcfIQ1SXw4u3kjtsM987+I/Cjt9n2Q5JCfCMzO5XkoZ0Wmb8G7mqkKE2LzLPxyezNZCw5KXmzL4MvnGfjynUrHPsgrjTuwAXuZVSvXbBIum4+7ddSeHTJ4biy53LgCfOaHB/DFTGX4YrVGyWt1SCSYiySpUnLL/S3lZTdfxOeoumwwnHH4t7EpyZlxaJ4kdevJYXHYFiYxpPLuML3Jtxr9V5c4Q2u3B9MYbgxQxL4TgI2N7NO1dOU5GtWNDUQ5DLj08PqWytxNrBWLhJhNdxzO+MG/D0pTX8jqZoZHORRMifi0WgbSJqAG+4mps9ZPZTXU0g1KXrsIkn75d79FsojUa4vXPcfkt6XRdakd38v4Evp3FfjKYYqkiqFaIsuYF9c2X92EqBWxA28SzNnzZQxiTWoiSKP8FkP+JOlujLJePoVXEj9ML6gPBAPec6UVeenU3weN2B3SboNTz93Brl0XvLIg8xY/hH8ObzHUoodM/uBpEdxI81V+HhwjaR34ukgT8AVrZPxegl/Tef6Yvr/VpKSXe5p+gh96ye04IJQMACS08GVuPHqYuBkeY2hpfF3+yV8nXI1LrxuA8yQ9FPcEL6ePIXjwcDHJd2e9p8sT+d5PB69lDEBr5OBeZrS1fF5+3Tzejk9lK+DO3Bv0i68f7Sn71VcaTIrXbdo3AmGjufxpeCW+Py9O/48DsLnoC3xvrVaer9n4s9uLdxxYFdcgToLN5hvjCtXn6EezfpNPLXoDNyhZzUzm5WMti+Z2clZY9Jc1Tp0txu8DcbjnuET8LXE8vh7u/cAjJ5V4LNJod6BO03doFwkSpJjoh7OfCYZTTcANkz/1sTXno/h0QFTLZduOe3/Z3xcz8uJ4/CI+bzjSxPuef6eZJT7AG6Qza61Qvp+HS7L/qUoeyaexQ2wxd/+UdhWxVMG3UQwv9gJdzptwdcby+IOFOfi6R1bgW9JejIZXaFvP2rFx4y78NTCB8rT+j5phVpvwegg6Sdukmfh+Bh15+I/4jJxK9Aq6SO4bLpn5vCJ96Of4I524FkL1sDXqaTjLxmO+wiGnoJz+/qUZL7AZdFOYF0K68ekI9ked+L4asmxwQgjjCijkwOp51HcE08vUaOuuGyTF+o+H3pzeJ6Dp6C4HjcM/NXMNpSnS9rOzD4nzzdfZBru0XMuvij9QTrnFrhR48tm9ttBtr930ZEUKF/EDTgrS8qKtR5nZj9L+wifiLbF6ylkaRq+aWZnyfNMZuk8ysLfarjH6zTVI1HWTuf+PH1ryYAvgqbhxY9bgS9Jyke1tOJGgf2B3y5ABpRG3GypJorc03sOzwozu1fSL4AL5HnwT8H7Y38LiHw6r7XkKeVm40azLklT8DHsajP7ZjrmGTwHbVav41q8YNf6ZvYvSfvg/aiPsXABYmNcgLwyKRAzL+ynko2jCVhI0pIlkRTr4oJib7o9SdsCpxWMCw+TU6onr/+ncUHVgKUk/Tt9bsI9vrLUX4vgCq8mvH/04O+bcK8w4WPfF/EQ6zy944qZXUpKeShptpmV5Z29Ji18Z+fsO9mHlwrb2vDc+lenc+6FK/WXwpV06+JeiLfg48lf5JF925hZPt3cmCGNyy1AZwPlwTuA3+NG+m78+b9pZpm3zm1yr+C7gZ3MbHrans8t/BR4H0rXLF5jT7weyy4paulh3DDSa8Q1s19Tj0xYCH9W16e2dCVjz5V4jvLseq+m6/VQNzB2AP+xlBYv/f5hPBIqGADmdWY2KY4t8qjBNvO6MxR+q+KefNfhdQimJgPw9njO4Q/jESW7Ap+0en0scOPMjNz3x/Exb4X0vZ1cHZx0vV1xQ2hmKFkK9ybsTsdOxKNoa/hYeZaZfW+Qf4pg8HTga9Cz8Sjhh8zsdnmE8k1mtqakY4AVzewZeUrILlwJ9hr1Of9DuLIMfD17hpn9Ln0/Cx/rj8SVYFk61zUorBnSmDRYB5BgGDCzGcCUgiJDzBmJ0gwsZ2aLyB3GzsJT//0AN9ifA5wvqSwSJdI4zn+uwdP0/haPdP8C8ICZHVu2s5k9QGG8B5CndT7WUq2CEpbDHSp+D9yJG02uwmXQO+fSxj5raUm74ymqTzGzw3PbMwN9MP+4AI9M/yRu0FoVX/c/go8HwmtwNSdD/dPAv6FXJrjDzHaVtDn1Oo7n4fLu+QSjkiTrXIBHBywDYGYbpd8+R6EmiqTFcQeybw3g9FVJk83s1nnd7mB4Ud05GxrUusnWlEmPWUvGuY3w8ebTuIy6H0nXEIxswogyOlkGrzGQGTS+C8zOFo6SzqNeLHEn3MPmF7hSYGX6L4aodNwkoGaeGuUOSafjCqsst+N4XOH5lvpQmpT2wpWh38vuJf12IX0HoCvS9weBk/GB5j/9nbug1DPg8mRgKUaiLIYvwOs7m80EdsobZwrnXxb3hl55oPe7oJCEhUZpjA7Dw2Cn4YqpdRsoXzPy6bweA96LKy3uwhVu6yfP5t50LGZ2UP4Ekj6EvxtZ/vppuEGwtC7PAsD+uDelQW9ffmGAffnjuMI7zzIUIi7M7AW8MP2GuW3vTNf7Ei5QHGYl6djM7FV5mqWnzaw9HXMiMNHMDhzIDUo6DvdS7qTuJfRk+t6MG92ONLMdcsc0J4X6RNwDeUlSigcr1H+Rp6RaFlekPIqntxsPrJkZb1K/3Aw30DRnkRhjjHfjESQdJV6WUDemvojPK+Nxw0oW9bMiPrY/A3xHUuatNQH3HH6fmZWlQFglKdD/ghvrtqZe3O9A4EFJvzCzv6brrAt8w8x2wQ05mWJ0MUlP4enpxgP/J+mZzCBcwhz3mBwIButEsEBjZj3Ji18lhlqgV6GEmfVkc0oyoNWsnnbwBdwY9jJuBFupYEABj4r7ZzrnZvjYvwNwjrz2xd9JQnGufVkdjEm44uMyMztB0il4pMJhuNF3X+ubOi4Yeh7F07D9AXgy9YkKsFwy1DfhitR/4c/1tRT99iZuBGnDvdWzftJELu+0pULPJcbaRYHvprV2FY84/IqZ/bi4YzCi6ROJIk/Re2/6+k+8JuNncANdZ+oHjSJRgvnPey1FnUJvxoV5jnlNtaUK1xpQIfqSOe4AXI7dR9JPzOzfDfYLhhF5esgNgCPwdeIzeGRB5uj3Cp7u9ZG0//JAeyY7JYe//0n7TsMjmPbE15cXDNNtBPMYebT7T3HZ8QzqUST9sRge3d7N3A2jTbhDThhRRhElekYy5+z0e59IFM2ZyQJczs1qOU/FHdpjbTGKCCPK6GQgi7dsn3vxEMQtgGXN7NOSPkjjdF5/ScftgxtcskWpkVOOm9mN+ADwVlgV9xpaHR9AviEpryBdkr5ef2fjytt7gIfNc9afQYN0Xvhkl8952wzsNohIlDxlOZTjvXlrzMKf4Wdxz55SS32OpZOydCJwIZ6e4U3cK+wBSVuZ1yroTT2VjHOPU6/bMQF4PXkJGe7NOgE3yixwdQ6SQmlnSbvgKXF6SR5yG+PKoe7Cb+vjeZ+LIaZL049Bs3COFtyTeB/gaEnX5o0LuciGR+diXMsWthSNE/JaUL8ws2MkvQe4DPdGfhPYsUzpmYwid0s6B0+PmHEUsJ+kPQpeQmfhKeI68b/JErhRxSSdTIqewJV7TXhdjgf7u5/RiJk9TnqHJa0HLFJQUE3C0yBOLB6b5qAr8fnpc7ix6tn025W4Ee3R3P6H4nPYRni+8f/gEZUn4+kysjY9JelM3Ni/ddq8NR5ZlBkMLSnHZpjZu5LB61Uza5jiT9K7mTOPevDWWQ9Pi9mDj8tL40NAZsBqwhWaNxYPlLS2mT2ErwuuBdbH6y19Q9Ih5qlCM7YA/ixpfzy6ZF8zuz69p6emdqwoaRHcqPNaMq4cic87p+N1NMAN0Efjc8dSeHrKZ/H0lecQDDVr4Mqo83Cjxo1mtl8/Ti0fxCMsW3Cl2Ib43N+UPoMbQ+a2DgHYxOrRcMcCa4cBZdRRoTwSBQDz2hfPDZUiPpj35I0ao+Fakr4ITMLrM/bgxvrNx6iTzWijgq8lfw5cmJw9tscVmweCZ/WQtEhy1ih7ZjUAM2tPTpg/xdOXR4TR6OX9uFy8MZ7FYq7P0sz+gddi3B2XI/tj8xQ5GYwuPiLpf3EnnBquk8rrLQW8krY1AePlUfiv5PZ5Lm94CUYfoQwevXwleT5ACi3PKSBWwgV9zFPJPC9Pv5XRAVxqZnsngWFbM9tL0g7UFaI3A9en417AQ1h7c79LWg33yDzBBpeuRnj6nofNbB95hMsdJZEovVjKPVrwDnwe+IJ5nvNbgJPN7LfydA5FXgAuzB3/qvqG3d3cT3vnyKGcCe39HDPmSAruOQrwNti3CjRb31zE2wA/xBeq2+D1Zh6UR02dZbkCnUnh9TXc6zRLl3GYmf1T0gW4Evtm4FpJ2yVlLuD5N5IiPSsKfU+KWDkWV5SeKulOcoaXBQl5MbMLgZ+Z2YvqW0jzJVJ6QEmftFSrRtJiuGBxiXk6hDzLUlcyznG5wvdvA4+Y2RWSPgGcLmn/nAfeqriC3ApefllR8v1y26p4bZdvpd+yiKTbgG8nRcmVuMHuD3iEwo2SpphZZijODDuX4vUXfoYblTOOxxfMv5F0oJmdDWBme+eO/wheK+oi3Oi8CO5V8h0bfK2f0cx6eK7oNQd435vhBqsj8PoE35cX/N4Zjx7Ys7B/e9p/TzObKelaPM/0eenZ5zmZvs9xJ7zvbYsb7QdDBY9c2BN3RpiD5IDwnJk9UfZ7MCfmKd3WyL6rn3Re6ff34grvc4FHJP0HX+fsSz1V277AfZLeMLNz5UXCP4nnGH4XnvItM8qcn7ZV8Hlmf+ALyVj2V9x4clW6xr1J+dWER0Gugtff+UY6d1ZHJxg6Kviadivz2nSbA3tL2g4f97NIlAowzcw+iRu4r02RS21pXfJ7fLyehKdiuZtcP+yHY+VpSK/Ax6sPzmX/YGSwEB6J2oYbTMoiUf42l3M0SucVjBIkfQ1PAznkcps8YvHULMIkt31f4MfAp9Ia5kQ8FeVNknazqJkxXzGzWwDkqWcvTJvbcIeJjK3wyNd78HlnfJp3wMea7ByLUE+d/Jo88nYrM7ttaO8imNeYpyLf0Lw22gq4nDxQFsHXI58r+zH1tQVSFzHaMbObyekOJX0caDKza9L3XfEsKIOumSmPcvsyC54eYdQxR+2CYFRQwesQrG9eyOgi3Bsy+34tcz7bCkmpaWYP5BSBlWxfM7suW2Sa54j+Jp726I/p33dy59sMz9u3wSDb/iF8oXFA7vpllBWhzt/DiWb2q5J7OM7q6T5I27ZJ93IPnvd+bdy7IEsP9k3KacY91x7K/8Nz4pYWyR7DrIJHdzyJLwpflReTPxXYNPuets0EZkmaJOlbkh7Ec9r/FtggGcU+itc+2AF4SNLfJf0oGWuuBCaZ2QZmdgQewfKqpBOAzYEzzexveH78P0k6Wn0tbANZlAwoFH8sIWkyXrTySupRKBNInjVpgT8Zj7L4aTpmIzw0vYP6O5t5ZO2BK5SebHDJFqBFUqukbwJ2VEASAAAHGUlEQVSfwMcMcIXn6sDUpIQGT6exEFA1s6bsH15o/szCtlb6hlWvh3uEfBEPu58KHG9m9+HCzlS8APkNkvJF0LMw+51xz/OsMJyZpxI6Fl/M9Kb8kbS4pCmSbsUNyR/F01rNxpWq7cDDks6XtE9S5o51LsAjwNbMbWtYdNnMfmhmhyfv7uuozzHrAlsXF45mdraZXWqeahHcOLZv+txEbjw2sxlm9gyApFWBtfGIl8OByyQthEc+ZJ6lzZSMB5KWwBWsu+FK85fwFGBLFHY9goHlPg5wg6ekamHMLu5TlbSQpJZkcL0OjzzZwMx2xN/nKTkDLOmZ7wxsIY8uOwZ41sx+b2Y/zxlQMLM3zOxQM8tSbZwMPJbe+RdxZfv16br/i/e12bgh7cfA/+Hrht+E8WxYaIJ6ui0zu8vMWlP0yQb4c14ZN2RPkddJ+Si+7sgiFK/Cx4E70/km4mPDMpKuLLzXfcYUvM7Sb3BHkGmE4mNEI2m8pOPxd/QY4AbcANoi6d2Slk8OJJ3AOslImzEeX++AK1H3TX1rGj43rYxHm0b6pZFHJ7BmUloDkNZfh+BRrI2oMkAnscK1+tRDk0fkHkpKp522rSLpGjw6dlfzGm0kOfUTpFTVko6T9I5BtiGY93Rb39Rq+ciDGvW1YhMpnVcaEw7BPc+XwOWs03BnjCtwuefCZMgPRhlWr422IzAtrUubi/vJGZffNJDTz4s2BvOHJKscjjtm5Z33uoFzJf2igQ7AgInympxFtsPnkQVOTzXaiEiU0UkrfSNRAFDfSJTTCseMo1yp1UbjAkg/wQu6l3EhLpA+3OD3Rvwc9yDOFinNuAfzIbl9FqPcu3NQ95C8QfbF08VUcOVHE774Fa4g+QLuEX8ZcLD1TWO0KI0jUcZcep7+SOGp4+a6Y460mNgBV1r8T94zy8wMuETSFXg9g88Cf0zbix5ZE3FhZTO8APWsdI4zJb0MLJYiUI7H63YsSr1OwUqSpuGp57qT4n91vMD9k2ZW6l0+RnkYVxZ+L/29TsQn6t7IDDO7R9LWuEIc/O/+KLB7ToENXpdoCl5M/ecNrteS/u2GK7S2MbOX03XeSEadw4HNJP0uKdTbS86TpejrpcRQeq+k1VJ0zUbAoWZ2XRKmq0Crmd0p6QP0FZb3xwWhbklr4orTcwvK2fMK7dkh3dNJ2diQ7mV8uoeTJZ2Ljz0fMrMxnw853fe22XdJl+NptOYwsMlTee0JLI57hK+BK613MrPrBni9fF+cQKF/5NgpnXtH4FU8PdS9eCq/h+Qe7afiBpwiE4H7gb3M04S14uP+v9K4A65wq+FGlmBgfAk4CC+q2EdIUN90XuPw+fk64Nf5d97MLkr7n4LPC19J2+/ClaWkOf03A2jPj3GBJ29keVHSj/HItipeO+VxM3sJOEbS+fj7HV5iw0NDgyzeT8ZB7zjUkYwm5+LOHBfhY9NJuFJrJdwZ42ncaNsMdJrZ9Nw5FyFXgNo83c4pkq7CjW43y9PwhAJkZPIO/NnuZJ5a52LcaecAfM5ZCp832nBZ4JFkSLkBlw9+l85TVH40SboUj2AaTAR+MDxcjr+fM3I2esPXsz/r57iGcnA/nI9HqJ2U29YNXGT1emyr4WuG2/Eab32iU8zs5eRE9C3csek3eC2OYD6Q5IUn1DdTRb5g9NJ4WlBwZ8GseDxmdomkWcBDwHlmdoY8SnoNfO7Z2aLuzahEHqF8MPABvN7mmcDO6Xln9UWfxeeS56k7FzcDOxb7U44qPu683uD3YAQjz9JxO+7ou35Bx3W1vI7aJcBtkjayvjVRnsId+V6VlNd7VPBot6PMrINgRKOQAUYfSZlTszGQR3Uo70WequcM4HLrJ4xW0lp4zutz53UbguEjWfu7gK7+Fquq50hvzpT6CyLymhXvA25JHtmDObapYHCc2/7VkS5AZJ7xoRh7+0jaAPfKudfM2gu/LYILlU/iETx/tiHMbS7PYT1T0viStiwMrIOH3MeCdZQhaR3cc/SRIb7ORDN7dSivEQwNyTv8XwUjyds5XwVY2UrqawWjj+RRrKJjRhDMCyStMpCxQtK4YgRuMLpITiDLW9RIG1PIa4Iejyu2iymtgwWY5BR4XyP9RjKkTrIoGD8mCSNKEARBEARBEARBEARBEARBEARBCVETJQiCIAiCIAiCIAiCIAiCIAiCoIQwogRBEARBEARBEARBEARBEARBEJQQRpQgCIIgCIIgCIIgCIIgCIIgCIISwogSBEEQBEEQBEEQBEEQBEEQBEFQQhhRgiAIgiAIgiAIgiAIgiAIgiAISggjShAEQRAEQRAEQRAEQRAEQRAEQQlhRAmCIAiCIAiCIAiCIAiCIAiCICghjChBEARBEARBEARBEARBEARBEAQlhBElCIIgCIIgCIIgCIIgCIIgCIKghP8HDpwJi4E665QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. 准备数据\n",
    "names = ['雷神3：诸神黄昏','正义联盟','东方快车谋杀案','寻梦环游记','全球风暴', '降魔传','追捕','七十七天','密战','狂兽','其它']\n",
    "y = [73853,57767,22354,15969,14839,8725,8716,8318,7916,6764,52222]\n",
    "x = range(len(names))\n",
    "\n",
    "\n",
    "# 2. 创建画布\n",
    "plt.figure(figsize=(20,8), dpi=100)\n",
    "# 3. 绘图\n",
    "plt.bar(x, y, width=0.5, color =['b','r','g','y','c','m'])\n",
    "\n",
    "# 添加刻度\n",
    "plt.xticks(x, names)\n",
    "\n",
    "# 添加网格\n",
    "plt.grid(True, linestyle='-.')\n",
    "\n",
    "# 添加标题\n",
    "plt.title(\"电影票房对比\", fontsize=20)\n",
    "\n",
    "# 4. 显示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
